E-Commerce
Shattering the limits of conventional commercial workflows
Hyperrealistic Virtual Influencers
Virtual influencers are rapidly transforming the landscape of e-commerce, signaling a shift toward digital-first consumer engagement. These AI-generated personas—designed with lifelike appearances, curated personalities, and targeted branding—offer businesses a new level of creative control and scalability in marketing. Unlike human influencers, virtual influencers can be endlessly customized, never face real-world controversies, and operate 24/7 across global platforms. This consistency and adaptability make them ideal for promoting products in fashion, beauty, tech, and lifestyle sectors.
E-commerce brands are increasingly leveraging virtual influencers to drive storytelling, create immersive experiences, and enhance personalization. Their presence on platforms like Instagram, TikTok, and the metaverse allows them to engage with younger, digitally native audiences in authentic, relatable ways. Consumers are drawn to their futuristic aesthetic, perfectly crafted content, and unique ability to blend entertainment with commerce.
Social Media Sub-graph Simulation
Creating social network graph subsets from popular social media platforms is a powerful method for simulating and understanding consumer behavior patterns in a digitally connected world. Social networks like Instagram, Twitter, Facebook, TikTok, and Reddit are rich with structured and unstructured interaction data—including follows, likes, comments, shares, and messaging—that can be modeled as graphs. In these graphs, users are nodes, and interactions or relationships between them form the edges. Subsetting these graphs—through sampling, community detection, or interest-based clustering—enables researchers and marketers to create manageable, focused datasets that preserve real-world dynamics while maintaining privacy and scalability.
By isolating subsets tied to specific behaviors (e.g., frequent buyers, trendsetters, brand advocates), brands can study diffusion of influence, opinion formation, and purchasing decisions in micro-environments. Graph algorithms like PageRank, centrality measures, and clustering coefficients help identify key influencers, subcommunities, and pathways of information flow. These insights can be used to simulate scenarios such as viral marketing, targeted advertising, and customer churn prediction.
